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Technical Briefs

Multiobjective Optimization for Integrated Tolerance Allocation and Fixture Layout Design in Multistation Assembly

[+] Author and Article Information
Z. Li

 Foxconn Technology Group, Sunnyvale, CA 94085

L. E. Izquierdo

Warwick Digital Lab, The University of Warwick, Coventry CV4 7AL, UK

M. Kokkolaras1

Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109

S. J. Hu, P. Y. Papalambros

Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109

1

Corresponding author.

J. Manuf. Sci. Eng 130(4), 044501 (Jul 08, 2008) (6 pages) doi:10.1115/1.2951951 History: Received October 20, 2006; Revised September 24, 2007; Published July 08, 2008

Cost and dimensional variation of products are significant attributes in multistation assembly processes. These attributes depend on product∕process tolerances and fixture layouts. Typically, tolerance allocation and fixture layout design are conducted separately without considering potential interrelations. In this work, we use multiobjective optimization for integrated tolerance allocation and fixture layout design to address interactions and to quantify tradeoffs among cost, product variation, and assembly process sensitivity. A nested optimization strategy is applied to a vehicle side frame assembly. Results demonstrate the presence and quantification of tradeoffs, based on which we introduce the concept of critical variation and critical budget requirements.

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Copyright © 2008 by American Society of Mechanical Engineers
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References

Figures

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Figure 1

Schematic of an automobile body structure assembly (1)

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Figure 2

Top and side views of the 3-2-1 fixture layout

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Figure 3

Relations among system inputs and major system attributes

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Figure 4

Nested optimization strategy for the problem of Eq. 8

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Figure 5

Example: vehicle side frame model

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Figure 6

Fixture layout in the rigid multistation assembly system

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Figure 7

Tradeoff between cost and sensitivity for σs=0.33mm

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Figure 8

Tradeoffs between cost and sensitivity for σs=0.22–0.33mm

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Figure 9

Relation between cost and sensitivity for σs=0.5–1.67mm

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Figure 10

Relation between variation and sensitivity for different budgets

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